Interagency Monitoring Of Protected Visual Environments Research Articles

Urban and rural coarse aerosol mass across the United States: Spatial and seasonal variability and long-term trends

Coarse aerosol mass (CM = PM10 − PM2.5, mass of particles with aerodynamic diameters between 2.5 and 10 μm) has important environmental and climate impacts. Examining the spatial and temporal variability of CM is important for understanding its sources and transport, evaluating its environmental impacts, and designing mitigation strategies. CM was computed at 195 collocated U.S. Environmental Protection Agency (EPA) PM10 and PM2.5 Federal Reference Method (FRM) sites from 2000 through 2016. These data were integrated with remote/rural CM data at 155 sites from the IMPROVE (Interagency Monitoring of Protected Visual Environments) network to create a continental-scale dataset of daily, monthly, seasonal, and annual mean CM concentrations, as well as regionally aggregated data. Annual mean average continental United States (CONUS) urban CM concentrations were twice that of rural CM concentrations (10.5 μg m−3 versus 4.9 μg m−3, respectively) for 2012–2016. The highest CM concentrations occurred in the Southwest in spring, the central United States in summer and fall, and southern California nearly year-round. The lowest CM concentrations occurred in the Intermountain West, northwestern United States, and regions in the East. While urban CM concentrations were higher, CONUS average urban and rural CM/PM10 fractions were similar, with an annual mean fraction of 0.5. However, many regions, especially across the West, experienced much higher fractions (>0.7) depending on season. Regional mean CM weekly cycles with lower weekend concentrations were observed at both urban and rural sites throughout most of the country, indicating anthropogenic influence. Trend analyses suggest spring and summer mean CM has increased significantly at some remote and urban sites over the 2000–2016 period, especially at sites in the central and eastern United States. However, CONUS annual mean urban CM has decreased significantly (p < 0.05) at a rate of −1.8% yr−1 compared to an insignificant increase of 0.5% yr−1 at rural sites. Urban and rural relative contributions of CM to PM10 have increased since 2000 due to the strong reductions of PM2.5 mass. Understanding CM seasonal and temporal variability, composition, and sources is increasingly important in order to develop effective mitigation strategies for managing its environmental and climate impacts.

An examination of the algorithm for estimating light extinction from IMPROVE particle speciation data

The Interagency Monitoring of Protected Visual Environments (IMPROVE) network is the basis for monitoring visibility in Class I Areas throughout the United States. Monitoring is conducted by collecting PM2.5 and PM10 samples every third day at over 150 remote and rural sites nationwide, with PM2.5 samples being analyzed for chemical composition. Light extinction is reconstructed using an algorithm that relates speciated mass to light extinction based on aerosol mass and size (second IMPROVE equation). In addition, the National Park Service directly measures light scattering at a subset of IMPROVE sites using Optec NGN-2 integrating nephelometers. The optical measurements serve as a check of the reconstructed scattering, in that measured scattering from the nephelometers and reconstructed scattering from the second IMPROVE equation should be equivalent. During its development, the second IMPROVE equation was shown to accurately estimate light scattering for a broad range of aerosol compositions and loadings for samples collected through 2003. Here reconstructed scattering is assessed from the second IMPROVE equation by comparing measured light scattering from nephelometers to reconstructed light scattering at 11 collocated sites over a 16 year period (2001–2016). The comparisons suggest that the relationship between measured and reconstructed light scattering has changed over time and that in recent years the second IMPROVE equation has underestimated light scattering at many sites. This shift toward poorer agreement corresponds to periods with relatively large decreases in sulfate and organic mass concentrations. These decreases lead to biases in reconstructed scattering calculated with the second IMPROVE equation, due to the assumed relationship between mass concentration and size distribution. This relationship, referred to as the split component algorithm, appears to be flawed as currently implemented. A potential approach is explored that scales the split component algorithm each year and at each site, based on measured mass concentrations at the site. The proposed approach appears to reduce the biases in the second IMPROVE equation.

Asian Long-Range Transport in Relation to Atmospheric Rivers in Northern California

The study investigates the effect of aerosol long-range transport on precipitation over Northern California during atmospheric river (AR) events in the 2017 cold season (January–April). ARs in 2017 were one of the strongest to date, and the intense precipitation associated with the ARs resulted in flooding, destruction of property, and contamination of water supplies. The Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) data shows Asian dust traveling across the Northern Pacific Ocean along with AR events. Aerosol measurements in California, provided by the Interagency Monitoring of Protected Visual Environments (IMPROVE), show that more Asian dust tends to be observed over the coast, while non-Asian/localized dust is observed inland. A mixture of Asian and localized dust is observed over the mountains, although higher amounts of both are observed in the spring (March–April). Back trajectory analysis confirms that Asian aerosols are transported along the air parcels, and each AR event has its own transport pattern in terms of horizontal advection and vertical lifting. Correlation between precipitation and aerosols is low. This suggests that aerosols contribute little to the decrease of local precipitation during the 2017 AR events.

Analysis of functional groups in atmospheric aerosols by infrared spectroscopy: systematic intercomparison of calibration methods for US measurement network samples

Abstract. Peak fitting (PF) and partial least squares (PLS) regression have been independently developed for estimation of functional groups (FGs) from Fourier transform infrared (FTIR) spectra of ambient aerosol collected on Teflon filters. PF is a model that quantifies the functional group composition of the ambient samples by fitting individual Gaussian line shapes to the aerosol spectra. PLS is a data-driven, statistical model calibrated to laboratory standards of relevant compounds and then extrapolated to ambient spectra. In this work, we compare the FG quantification using the most widely used implementations of PF and PLS, including their model parameters, and also perform a comparison when the underlying laboratory standards and spectral processing are harmonized. We evaluate the quantification of organic FGs (alcohol COH, carboxylic COOH, alkane CH, carbonyl CO) and ammonium, using external measurements (organic carbon (OC) measured by thermal optical reflectance (TOR) and ammonium by balance of sulfate and nitrate measured by ion chromatography). We evaluate our predictions using 794 samples collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA) in 2011 and 238 laboratory standards from Ruthenburg et al. (2014) (available at https://doi.org/10.1016/j.atmosenv.2013.12.034). Each model shows different biases. Overall, estimates of OC by FTIR show high correlation with TOR OC. However, PLS applied to unprocessed (raw spectra) appears to underpredict oxygenated functional groups in rural samples, while other models appear to underestimate aliphatic CH bonds and OC in urban samples. It is possible to adjust model parameters (absorption coefficients for PF and number of latent variables for PLS) within limits consistent with calibration data to reduce these biases, but this analysis reveals that further progress in parameter selection is required. In addition, we find that the influence of scattering and anomalous transmittance of infrared in coarse particle samples can lead to predictions of OC by FTIR which are inconsistent with TOR OC. We also find through several means that most of the quantified carbonyl is likely associated with carboxylic groups rather than ketones or esters. In evaluating state-of-the-art methods for FG abundance by FTIR, we suggest directions for future research.

Impacts of short-term mitigation measures on PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; and radiative effects: a case study at a regional background site near Beijing, China

Abstract. Measurements at a background site near Beijing showed that pollution controls implemented during the 19th National Congress of the Communist Party of China (NCCPC) were effective in reducing PM2.5. Mass concentrations of PM2.5 and its major chemical components were 20.6 %–43.1 % lower during the NCCPC-control period compared with a non-control period, and differences were greater on days with stable meteorological conditions. A receptor model showed that PM2.5 from traffic-related emissions, biomass burning, industrial processes, and mineral dust was 38.5 %–77.8 % lower during the NCCPC-control versus non-control period, but differences in PM2.5 from coal burning were small, and secondary sources were higher during the NCCPC-control period. During one pollution episode in the non-control period, secondary sources dominated, and the WRF-Chem model showed that the Beijing–Tianjin–Hebei (BTH) region contributed 73.6 % of PM2.5 mass. A second pollution episode was linked to biomass burning, and BTH contributed 46.9 % of PM2.5 mass. Calculations based on Interagency Monitoring of Protected Visual Environments (IMPROVE) algorithms showed that organic matter was the largest contributor to light extinction during the non-control period whereas NH4NO3 was the main contributor during the NCCPC. The Tropospheric Ultraviolet and Visible radiation model showed that the average direct radiative forcing (DRF) values at the Earth's surface were −14.0 and −19.3 W m−2 during the NCCPC-control and non-control periods, respectively, and the DRF for the individual PM2.5 components were 22.7 %–46.7 % lower during the NCCPC. The information and dataset from this study will be useful for developing air pollution control strategies in the BTH region and for understanding associated aerosol radiative effects.

Aerosol Optical Thickness: Organic Composition, Associated Particle Water, and Aloft Extinction

Over the contiguous United States, the strongest remotely sensed aerosol optical thickness (AOT) is observed in the east, where aerosol liquid water (ALW) and extinction per unit PM2.5 dry mass are highest. Positive associations between ALW due to sulfate and nitrate with remotely sensed AOT offer a contributing explanation for geospatial patterns in AOT seasonality. We seek to further resolve patterns in ALW-AOT relationships by investigating organic mass (OM) fractionation, converted from organic carbon (OC) measurements using regionally specific OM:OC ratios, and the associated impacts on ALW. ALW is integrated from the surface through the boundary layer and estimated from measured particle chemical composition using ISORROPIAv2.1 and κ-Kohler theory at eight Interagency Monitoring of PROtected Visual Environments (IMPROVE) sites in areas of contrasting AOT seasonality. Two groups of four sites each, clustered by chemical climatology, are compared to AOT derived from the Moderate Resolution Imaging Spe...

Trends in remote PM2.5 residual mass across the United States: Implications for aerosol mass reconstruction in the IMPROVE network

The Interagency Monitoring of Protected Visual Environments (IMPROVE) network collects aerosol samples for gravimetric and composition analysis in support of the Environmental Protection Agency's Regional Haze Rule and for long-term trend studies and model evaluations. Reconstructing PM2.5 mass or extinction from composition measurements requires assumptions of the molecular form of the individual species assumed to compose the bulk of PM2.5 mass. The IMPROVE reconstruction algorithm includes sulfate as ammonium sulfate, nitrate as ammonium nitrate, organic mass calculated with an assumed organic carbon (OC) to organic mass (OM) multiplier (OM/OC) of 1.8, elemental carbon, fine dust assuming common mineral oxides in soil, and sea salt calculated from chloride. Comparisons of reconstructed fine mass (RCFM) to PM2.5 gravimetric fine mass (FM) provide a check on these assumptions as well as help identify possible biases in gravimetric or speciated measurements. Significant changes in aerosol concentration and composition have occurred over time, leading to decreased FM across the United States. However, within the IMPROVE network, annual mean FM and RCFM have decreased at different rates from 2005 through 2016 (−29% versus −43%, respectively), causing the network median residuals (FM − RCFM) to increase by 0.49 μg m−3 over the 12-year period. The residual shifted from mostly negative before 2011 to mostly positive after 2011, with a strong summer peak. A multiple linear regression analysis indicated that FM biases increased due to the presence of particle-bound water (PBW) after 2011, associated with increased laboratory relative humidity during weighing. Results also suggested that the OM/OC ratio increased across the network after 2011, unrelated to the influence of PBW. While temporal behavior in the OM/OC ratio was similar across the network and for all seasons, values were highest in the East and during summer. Fine dust also appeared to be underestimated by ∼20%. Identifying the source of the trends in the FM residual is essential for accurately estimating contributions by individual species to RCFM and visibility degradation.

Source sector and region contributions to black carbon and PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; in the Arctic

Abstract. The impacts of black carbon (BC) and particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) emissions from different source sectors (e.g., transportation, power, industry, residential, and biomass burning) and geographic source regions (e.g., Europe, North America, China, Russia, central Asia, south Asia, and the Middle East) to Arctic BC and PM2.5 concentrations are investigated through a series of annual sensitivity simulations using the Weather Research and Forecasting – sulfur transport and deposition model (WRF-STEM) modeling framework. The simulations are validated using observations at two Arctic sites (Alert and Barrow Atmospheric Baseline Observatory), the Interagency Monitoring of Protected Visual Environments (IMPROVE) surface sites over the US, and aircraft observations over the Arctic during spring and summer 2008. Emissions from power, industrial, and biomass burning sectors are found to be the main contributors to the Arctic PM2.5 surface concentration, with contributions of ∼ 30 %, ∼ 25 %, and ∼ 20 %, respectively. In contrast, the residential and transportation sectors are identified as the major contributors to Arctic BC, with contributions of ∼ 38 % and ∼ 30 %. Anthropogenic emissions are the most dominant contributors (∼ 88 %) to the BC surface concentration over the Arctic annually; however, the contribution from biomass burning is significant over the summer (up to ∼ 50 %). Among all geographical regions, Europe and China have the highest contributions to the BC surface concentrations, with contributions of ∼ 46 % and ∼ 25 %, respectively. Industrial and power emissions had the highest contributions to the Arctic sulfate (SO4) surface concentration, with annual contributions of ∼ 43 % and ∼ 41 %, respectively. Further sensitivity runs show that, among various economic sectors of all geographic regions, European and Chinese residential sectors contribute to ∼ 25 % and ∼ 14 % of the Arctic average surface BC concentration. Emissions from the Chinese industry sector and European power sector contribute ∼ 12 % and ∼ 18 % of the Arctic surface sulfate concentration. For Arctic PM2.5, the anthropogenic emissions contribute &gt; ∼ 75 % at the surface annually, with contributions of ∼ 25 % from Europe and ∼ 20 % from China; however, the contributions of biomass burning emissions are significant in particular during spring and summer. The contributions of each geographical region to the Arctic PM2.5 and BC vary significantly with altitude. The simulations show that the BC from China is transported to the Arctic in the midtroposphere, while BC from European emission sources are transported near the surface under 5 km, especially during winter.

Long-Term Strategy for Assessing Carbonaceous Particulate Matter Concentrations from Multiple Fourier Transform Infrared (FT-IR) Instruments: Influence of Spectral Dissimilarities on Multivariate Calibration Performance.

Matching the spectral response between multiple spectrometers is a mandatory procedure when developing robust calibrations whose prediction is independent of instrument-related signal variations. A viable alternative to complex calibration transfer methods consists of matching the instrument spectral response by controlling a set of key instrumental and environmental parameters. This paper discusses the applicability of such an approach to three Fourier transform infrared (FT-IR) spectrometers used for the routine assessment of carbonaceous particulate matter concentrations in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) speciation network. The effectiveness of the proposed matching procedure is evaluated by comparing the spectral response for each individual instrument in order to characterize the extent, and nature, of the remaining inter-instrument spectral dissimilarities. Instrument-related contributions to the signal were determined to be small compared with the spectral variability induced by the filter type used for sample collection. The impact of spectral differences on prediction was addressed through the comparison of model performance derived from multiple calibration scenarios. A hybrid model yielding accurate and homogeneous prediction regardless of the instrument was proposed for organic carbon (OC) and elemental carbon (EC), two major constituents of atmospheric particulate matter. Coefficients of determination of 0.98 (OC) and 0.90 (EC) with median biases not exceeding 0.20 µg (OC) and 0.07 µg (EC) are reported. The long-term stability, assessed from weekly measurements of reference samples, shows a deviation in predicted concentrations of less than ±5% over a 2.5-year period for most of the data collected. Extending OC and EC hybrid models to the prediction of ambient samples collected during the two subsequent years provides satisfactory performance. The proposed instrument matching procedure coupled with the relative simplicity of the hybrid model is an alternative to computationally advanced calibration transfer methodologies for the characterization of carbonaceous particulate matter using multiple FT-IR instruments.

Decreasing Vanadium Footprint of Bunker Fuel Emissions.

The Interagency Monitoring of Protected Visual Environments (IMPROVE) network measures the chemical composition of atmospheric particulate matter at over 160 locations throughout the United States. As part of the routine quality control process, we noted decreases in the network-wide vanadium (V) and nickel (Ni) concentrations in 2015 relative to the previous years. Enriched V and Ni with respect to soil are indicative of heavy fuel oil burning and are often used as tracers for emissions from marine vessels. Multiple regulations on the fuel used by marine vessels were implemented in North America since 2010, and the most sweeping regulation was implemented at the start of 2015. The 2015 regulations reduced the allowable fuel oil sulfur concentrations within the North America Emissions Control Area from 1.0% to 0.1% to reduce the environmental and human health impacts of sulfates. As a side effect, these requirements economically favored fuels with lower V and Ni concentrations. The atmospheric concentrations of V and Ni decreased markedly at many IMPROVE monitoring sites, particularly sites near major ports. Between 2011 and 2015, annual mean V concentrations measured on IMPROVE samples collected near the ports of Seattle, Washington and New Orleans, Louisiana decreased by 35% and 85%, respectively. These decreases have brought the coastal V and Ni concentrations much closer to those measured far inland.

US particulate matter air quality improves except in wildfire-prone areas

Using data from rural monitoring sites across the contiguous United States, we evaluated fine particulate matter (PM2.5) trends for 1988-2016. We calculate trends in the policy-relevant 98th quantile of PM2.5 using Quantile Regression. We use Kriging and Gaussian Geostatistical Simulations to interpolate trends between observed data points. Overall, we found positive trends in 98th quantile PM2.5 at sites within the Northwest United States (average 0.21 ± 0.12 µg·m-3·y-1; ±95% confidence interval). This was in contrast with sites throughout the rest of country, which showed a negative trend in 98th quantile PM2.5, likely due to reductions in anthropogenic emissions (average -0.66 ± 0.10 µg·m-3·y-1). The positive trend in 98th quantile PM2.5 is due to wildfire activity and was supported by positive trends in total carbon and no trend in sulfate across the Northwest. We also evaluated daily moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) for 2002-2017 throughout the United States to compare with ground-based trends. For both Interagency Monitoring of Protected Visual Environments (IMPROVE) PM2.5 and MODIS AOD datasets, we found positive 98th quantile trends in the Northwest (1.77 ± 0.68% and 2.12 ± 0.81% per year, respectively) through 2016. The trend in Northwest AOD is even greater if data for the high-fire year of 2017 are included. These results indicate a decrease in PM2.5 over most of the country but a positive trend in the 98th quantile PM2.5 across the Northwest due to wildfires.

Open-path, closed-path, and reconstructed aerosol extinction at a rural site

ABSTRACTThe Handix Scientific open-path cavity ringdown spectrometer (OPCRDS) was deployed during summer 2016 in Great Smoky Mountains National Park (GRSM). Extinction coefficients from the relatively new OPCRDS and from a more well-established extinction instrument agreed to within 7%. Aerosol hygroscopic growth (f(RH)) was calculated from the ratio of ambient extinction measured by the OPCRDS to dry extinction measured by a closed-path extinction monitor (Aerodyne’s cavity-attenuated phase shift particulate matter extinction monitor [CAPS PMex]). Derived hygroscopicity (relative humidity [RH] < 95%) from this campaign agreed with data from 1995 at the same site and time of year, which is noteworthy given the decreasing trend for organics and sulfate in the eastern United States. However, maximum f(RH) values in 1995 were less than half as large as those recorded in 2016—possibly due to nephelometer truncation losses in 1995. Two hygroscopicity parameterizations were investigated using high-time-resolution OPCRDS+CAPS PMex data, and the κext model was more accurate than the gamma model. Data from the two ambient optical instruments, the OPCRDS and the open-path nephelometer, generally agreed; however, significant discrepancies between ambient scattering and extinction were observed, apparently driven by a combination of hygroscopic growth effects, which tend to increase nephelometer truncation losses and decrease sensitivity to the wavelength difference between the two instruments as a function of particle size. There was not a statistically significant difference in the mean reconstructed extinction values obtained from the original and the revised IMPROVE (Interagency Monitoring of Protected Visual Environments) equations. On average, IMPROVE reconstructed extinction was ~25% lower than extinction measured by the OPCRDS, which suggests that the IMPROVE equations and 24-hr aerosol data are moderately successful in estimating current haze levels at GRSM. However, this conclusion is limited by the coarse temporal resolution and the low dynamic range of the IMPROVE reconstructed extinction.Implications: Although light extinction, which is directly related to visibility, is not directly measured in U.S. National Parks, existing IMPROVE protocols can be used to accurately infer visibility for average humidity conditions, but during the large fraction of the year when humidity is above or below average, accuracy is reduced substantially. Furthermore, nephelometers, which are used to assess the accuracy of IMPROVE visibility estimates, may themselves be biased low when humidity is very high. Despite reductions in organic and sulfate particles since the 1990s, hygroscopicity, particles’ affinity for water, appears unchanged, although this conclusion is weakened by the previously mentioned nephelometer limitations.

Visibility impacts at Class I areas near the Bakken oil and gas development

ABSTRACTOil and gas activities have occurred in the Bakken region of North Dakota and nearby states and provinces since the 1950s but began increasing rapidly around 2008 due to new extraction methods. Three receptor-based techniques were used to examine the potential impacts of oil and gas extraction activities on airborne particulate concentrations in Class I areas in and around the Bakken. This work was based on long-term measurements from the Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network. Spatial and temporal patterns in measured concentrations were examined before and after 2008 to better characterize the influence of these activities. A multisite back-trajectory analysis and a receptor-based source apportionment model were used to estimate impacts. Findings suggest that recent Bakken oil and gas activities have led to an increase in regional fine (PM2.5—particles with aerodynamic diameters <2.5 µm) soil and elemental carbon (EC) concentrations, as well as coarse mass (CM = PM10–PM2.5). Influences on sulfate and nitrate concentrations were harder to discern due to the concurrent decline in regional emissions of precursors to these species from coal-fired electric generating stations. Impacts were largest at sites in North Dakota and Montana that are closest to the most recent drilling activity.Implications: The increase in oil and gas activities in the Bakken region of North Dakota and surrounding areas has had a discernible impact on airborne particulate concentrations that impact visibility at protected sites in the region. However, the impact has been at least partially offset by a concurrent reduction in emissions from coal-fired electric generating stations. Continuing the recent reductions in flaring would likely be beneficial for the regional visual air quality.

Separation of brown carbon from black carbon for IMPROVE and Chemical Speciation Network PM2.5 samples

ABSTRACTThe replacement of the Desert Research Institute (DRI) model 2001 with model 2015 thermal/optical analyzers (TOAs) results in continuity of the long-term organic carbon (OC) and elemental carbon (EC) database, and it adds optical information with no additional carbon analysis effort. The value of multiwavelength light attenuation is that light absorption due to black carbon (BC) can be separated from that of brown carbon (BrC), with subsequent attribution to known sources such as biomass burning and secondary organic aerosols. There is evidence of filter loading effects for the 25% of all samples with the highest EC concentrations based on the ratio of light attenuation to EC. Loading corrections similar to those used for the seven-wavelength aethalometer need to be investigated. On average, nonurban Interagency Monitoring of PROtected Visual Environments (IMPROVE) samples show higher BrC fractions of short-wavelength absorption than urban Chemical Speciation Network (CSN) samples, owing to greater influence from biomass burning and aged aerosols, as well as to higher primary BC contributions from engine exhaust at urban sites. Sequential samples taken during an Everglades National Park wildfire demonstrate the evolution from flaming to smoldering combustion, with the BrC fraction increasing as smoldering begins to dominate the fire event.Implications: The inclusion of seven wavelengths in thermal/optical carbon analysis of speciated PM2.5 (particulate matter with an aerodynamic diameter ≤2.5 μm) samples allows contributions from biomass burning and secondary organic aerosols to be estimated. This separation is useful for evaluating control strategy effectiveness, identifying exceptional events, and determining natural visibility conditions.

Recommended metric for tracking visibility progress in the Regional Haze Rule

ABSTRACTFor many national parks and wilderness areas with special air quality protections (Class I areas) in the western United States (U.S.), wildfire smoke and dust events can have a large impact on visibility. The U.S. Environmental Protection Agency’s (EPA) 1999 Regional Haze Rule used the 20% haziest days to track visibility changes over time even if they are dominated by smoke or dust. Visibility on the 20% haziest days has remained constant or degraded over the last 16 yr at some Class I areas despite widespread emission reductions from anthropogenic sources. To better track visibility changes specifically associated with anthropogenic pollution sources rather than natural sources, the EPA has revised the Regional Haze Rule to track visibility on the 20% most anthropogenically impaired (hereafter, most impaired) days rather than the haziest days. To support the implementation of this revised requirement, the EPA has proposed (but not finalized) a recommended metric for characterizing the anthropogenic and natural portions of the daily extinction budget at each site. This metric selects the 20% most impaired days based on these portions using a “delta deciview” approach to quantify the deciview scale impact of anthropogenic light extinction. Using this metric, sulfate and nitrate make up the majority of the anthropogenic extinction in 2015 on these days, with natural extinction largely made up of organic carbon mass in the eastern U.S. and a combination of organic carbon mass, dust components, and sea salt in the western U.S. For sites in the western U.S., the seasonality of days selected as the 20% most impaired is different than the seasonality of the 20% haziest days, with many more winter and spring days selected. Applying this new metric to the 2000–2015 period across sites representing Class I areas results in substantial changes in the calculated visibility trend for the northern Rockies and southwest U.S., but little change for the eastern U.S.Implications: Changing the approach for tracking visibility in the Regional Haze Rule allows the EPA, states, and the public to track visibility on days when reductions in anthropogenic emissions have the greatest potential to improve the view. The calculations involved with the recommended metric can be incorporated into the routine IMPROVE (Interagency Monitoring of Protected Visual Environments) data processing, enabling rapid analysis of current and future visibility trends. Natural visibility conditions are important in the calculations for the recommended metric, necessitating the need for additional analysis and potential refinement of their values.

A THTEE-DIMENSIONAL VARIATIONAL ASSIMILATION SCHEME FOR SATELLITE AOD

Abstract. A three-dimensional variational data assimilation scheme is designed for satellite AOD based on the IMPROVE (Interagency Monitoring of Protected Visual Environments) equation. The observation operator that simulates AOD from the control variables is established by the IMPROVE equation. All of the 16 control variables in the assimilation scheme are the mass concentrations of aerosol species from the Model for Simulation Aerosol Interactions and Chemistry scheme, so as to take advantage of this scheme in providing comprehensive analyses of species concentrations and size distributions as well as be calculating efficiently. The assimilation scheme can save computational resources as the IMPROVE equation is a quadratic equation. A single-point observation experiment shows that the information from the single-point AOD is effectively spread horizontally and vertically.

Comparison of elemental and organic carbon measurements between IMPROVE and CSN before and after method transitions

During a transition period from 2007 to 2009, the Chemical Speciation Network (CSN) altered its carbon sampling instrumentation and analysis methods to be more consistent with the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. CSN and IMPROVE operated collocated samplers spanning the transition at eight sites. This paper compares elemental, organic, and total carbon (EC, OC, and TC, respectively) measurements at these collocated sites from 2005 through March 2016. Prior to the changes, the concentration measurements between the two networks had imprecisions of 17, 17, and 16% and biases of 0.22, −1.93, and −1.69 μg m−3 for EC, OC, and TC, respectively, with CSN measuring higher OC and TC than IMPROVE. After the sampling equipment and analytical methods were changed, the imprecision improved to 14, 12, and 10% and biases decreased to −0.02, −0.12, and −0.15 μg m−3 for EC, OC, and TC, respectively. The increased comparability, particularly the smaller biases, between the two networks facilitates comparisons between urban and rural aerosols in geospatial analyses.

Effects of Chemical Composition of PM2.5 on Visibility in a Semi-Rural City of Sichuan Basin

The rate of visibility deterioration in Ya’an city in the Sichuan Basin has been accelerating since the 2000s. Issues related to the air quality as well as meteorological conditions are reported in this study. Fine particulate matters (PM2.5) were collected in Ya’an from June 2013 till June 2014. The chemical compositions of the samples were determined. The annual average visual range (VR), PM2.5 concentrations, and ambient light extinction coefficient (bext) were 11.9 ± 9.2 km, 64.1 ± 41.6 µg m–3, and 452 ± 314 Mm–1, respectively. The highest concentration of PM2.5, the highest bext, and the lowest VR were all seen in winter, followed by spring, autumn, and summer. Organic matter (OM), ammonium sulfate [(NH4)2SO4], and ammonium nitrate [NH4NO3] were the major constituents, accounting for 32.8%, 28.3%, and 12.1%, respectively, of the total PM2.5 mass. The revised Interagency Monitoring of Protected Visual Environments (IMPROVE) equation was applied to estimate ambient bext. On an annual basis, (NH4)2SO4 was the most significant contributor (43.1%), followed by OM (27.1%) and NH4NO3 (22.4%), which, in total, accounted for 92.6% of the ambient bext. Rayleigh, elemental carbon, fine soil, nitrogen dioxide, and chloride salt accounted for a minor fraction (7.4%). Up to ~40.8% of the ambient bext was ascribed to relative humidity (RH), of which 26.4% and 14.0% were attributed to the hygroscopic growth of (NH4)2SO4 and NH4NO3, respectively. More efforts are needed to reduce the average daily PM2.5 concentration of < 59 µg m–3 to avoid the occurrence of haze under a high average RH of 78.3 ± 10%, which significantly impacts visibility through various physico-chemical processes. Emissions of precursor gases, such as sulfur dioxide, nitrogen oxides, ammonia, and volatile organic compounds, should be reduced to improve the air quality and visibility in Ya’an.

Comparison of parameterizations for the atmospheric extinction coefficient in Lin'an, China

A more precise atmospheric extinction coefficient would be advantageous for improving air quality (visibility) forecasting. In this study, the size distribution, chemical composition and relative humidity were measured in Lin'an from January 9 to 31, 2015. The merits and weaknesses of three parameterization schemes are discussed in this paper, including the non-linear fitting scheme, the IMPROVE (Interagency Monitoring of Protected Visual Environment) algorithm and the κ-elemental carbon (EC)-Mie model. Comparing the three schemes mentioned above, we find that the non-linear fitting equation requires the least amount of data, and its calculation process is the simplest. However, its calculated values are significantly influenced by specific data and fitting formulas. The uncertainty of the variable coefficients makes it difficult to directly implement this method for other datasets. The calculated values of the three versions of the IMPROVE algorithm strongly correlate with the measured values, with slopes near 1.0 and statistical indexes (R2) of 0.848, 0.858 and 0.866. However, this method is affected by the chemical compositions of the particles in different regions; for example, when the quality of PM2.5 is reconstructed from the measured data, the coefficients of different components change, thus affecting the final results. The κ-EC-Mie model objectively reflects the changes in the law of visibility, as the model considers both the chemical composition and size distribution of particles, and its predominant merit is derived from the fact that it is calculated without an empirical formula, which may eliminate the computational errors caused by the uncertainties of coefficients.

Tailored coefficients in the algorithm to assess reconstructed light extinction at urban sites: A comparison with the IMPROVE revised approach

Estimates of light extinction and visibility are routinely performed by the U.S. Interagency Monitoring of Protected Visual Environments (IMPROVE) network using a simple algorithm which assesses light extinction coefficient (bext) at remote and rural sites from concentrations of major particulate matter (PM) species, NO2, and Rayleigh scattering from clear-air gaseous components. Following the same approach, in this paper an equation with tailored (i.e. site-specific) coefficients was implemented with the aim of reducing uncertainties and assumptions of the IMPROVE algorithm for applications at polluted urban sites. Major differences compared to IMPROVE algorithm are: 1) dry mass extinction efficiencies calculated using a discrete dipole approximation code with aerosol size distributions measured at our monitoring site as input data; 2) site-specific water growth functions computed separately for ammonium sulfate, ammonium nitrate, and organic matter; 3) fine soil evaluated using an equation previously adopted at our urban site; 4) aerosol absorption component assessed directly through filter-based optical measurements. Details about the calculations performed are reported in the paper and the comparison with the IMPROVE revised algorithm is discussed.The tailored approach here proposed to estimate reconstructed light extinction was applied to PM2.5 test samples collected on purpose in Milan (Italy), where heavy pollution episodes occur during winter periods. In addition, visual range was calculated applying the Koschmieder equation and compared to visibility measured at the nearby Milano-Linate airport obtaining a fairly good correlation.